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AI and ML has made it easier to utilize the mammoth amount of data available over the web. The raw or unstructured data can be used to get useful and actionable insights that can help businesses to grow and succeed. It needs to perform a lot of processes to train the machine learning models that can deliver valuable outcomes. There are 2 techniques that play critical role viz Data Annotation and Data Labelling.
Data annotation is the categorization and labelling of data for AI applications, which is done to achieve a specific use case in relation to the business problem you are trying to solve. We have experienced annotators to annotate these data for machine learning application. Even though data annotation and labelling are different they are used interchangeably many times.
Data annotation is the technique of labelling the data so that the machine can understand and memorize it. Whereas labelling attaches some meaning to the different types of data so that a machine can be trained in a machine learning model.
We do annotation for different types of data annotation modalities, depending on what kind of form the data is in. It can range from image and video annotation, text categorization, semantic annotation, and content categorization. We use some of the best open source and proprietary Annotation / Labelling tool for executing your projects.
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